One of the most important applications of multi-objective optimization is adjusting parameters ofpractical engineering problems in order to produce a more desirable outcome. In this paper, the decoupled sliding mode control technique (DSMC) is employed to stabilize an inverted pendulum which is a classic example of inherently unstable systems. Furthermore, a new Multi-Objective Particle Swarm O...

The application of multi objective model predictive control approaches is significantly limited with computation time associated with optimization algorithms. Metaheuristics are general purpose heuristics that have been successfully used in solving difficult optimization problems in a reasonable computation time. In this work , we use and compare two multi objective metaheuristics, Multi-Object...

The following MOEA algorithms are briefly summarized and compared: • NPGA Niched Pareto Genetic Algorithm (1994) – NPGA II (2001) • NSGA Non-dominated Sorting Genetic Algorithm (1994) – NSGA II (2000) • SPEA Strength Pareto Evolutionary Algorithm (1998) – SPEA2 (2001) – SPEA2+ (2004) – ISPEA Immunity SPEA (2003) • PAES Pareto Archived Evolution Strategy (2000) – M-PAES Mimetic PAES (2000) • PES...

PURPOSE To alleviate the intrinsic limitation of current time-of-flight magnetic resonance angiography (TOF-MRA) techniques, which are insensitive to in-plane blood flow due to the flow saturation effect. MATERIALS AND METHODS A multi-oblique-stack acquisition (MOSA) technique was proposed in this study to tackle this TOF problem by acquiring two or more TOF image stacks bearing different ori...

Particle Swarm Optimization (PSO) has received increased attention in the optimization research community since its first appearance. Regarding multi-objective optimization, a considerable number of algorithms based on Multi-Objective Particle Swarm Optimizers (MOPSOs) can be found in the specialized literature. Unfortunately, no experimental comparisons have been made in order to clarify which...

A multi-objective particle swarm optimization (MOPSO) approach is presented for generating Pareto-optimal solutions for reservoir operation problems. This method is developed by integrating Pareto dominance principles into particle swarm optimization (PSO) algorithm. In addition, a variable size external repository and an efficient elitist-mutation (EM) operator are introduced. The proposed EM-...